I have applied a range of statistical methods and developed software platforms and analytical tools to process and analyze large-scale sequencing datasets. These tools facilitate the discovery of patterns and similarities across diverse omics datasets, enabling the construction of statistical models that support robust hypothesis generation.
In various projects, I have integrated data from multiple sources, including:
Examples consist of:
Survival analysis: the Kaplan-Meier Estimator and the Cox Proportional Hazards Model
Regression analysis: incl. linear regression
Classification Methods: incl. logistic regression, elastic net, random forests, and support vector machines (SVMs), positive-unlabelled (PU) learning
Unsupervised Methods, e.g., PCA, MOFA, autoencoders